Making banking effective for the poor

In India, PhD student Natalia Rigol aims to tap into community knowledge to vet loan and grant applicants.

Graduate student Natalia Rigol has followed an unusual path to MIT: Her childhood in Cuba was tainted by poverty, and then her entire family received hard-to-come-by visas, enabling her to live out her elementary and middle school years in Russia and the Czech Republic — but with little understanding of the local languages.

When she was 13, Rigol’s family settled in the United States, where she finally had access to a middle-class life and a more stable education. Now, she is finishing up her PhD in economics, focusing on the use of finance to help poor individuals break the cycle of poverty.

“I often feel that I’m the product of extraordinary circumstances,” Rigol says. “But you shouldn’t have to be extremely fortunate, like I have been, just to live a decent life.”

Through field research in India, Rigol is hoping to devise alternative ways to deliver financing to poverty-stricken communities. For someone who’s still relatively young, she’s been at it for a while: Her work in this discipline — which she classifies primarily as “development work,” and secondarily as economics — has been ongoing since 2007, when she was an undergraduate at Harvard University.

Community banking

For the past few years, Rigol has spent about half her time living in India. Critical to her work is a deep understanding of how communities and social networks — in real life, not online — function in banking and finance: Beyond collecting data on people’s financial habits or entrepreneurial behaviors, she aims to understand neighborhood relationships by conducting in-depth interviews with residents.

Banking in the U.S. is predicated on federally regulated information, such as income, wealth, and credit histories. Access to credit cards and loans, both of which are essential parts of a person’s financial life, is based on robust and reliable data about the applicant’s financial situation.

But in many poorer settings, this type of data is simply unavailable, so decisions about who gets money, how much they get, and whether and how quickly they have to pay it back are difficult to make. As a rule, large banks don’t lend to the poor, while microfinance institutions do, but under very restrictive conditions. This can back borrowers into a financial corner — or leave potentially successful business owners penniless and out of luck.

To combat this, Rigol is hoping to tap into existing community knowledge about individuals as a source of relevant information that a bank could consult to vet a borrower or a grant applicant. The economies in the neighborhoods where she works in India tend to be based on small businesses and shops, so the process she is developing is mostly geared toward figuring out who has the potential to engage in successful entrepreneurship.

“I want to see if, under certain circumstances, people can reliably and accurately predict entrepreneurial success in a friend or neighbor,” she says.

Rigol has recruited 1,500 microentrepreneurs to participate in her study, and will randomly select one-third to receive $100 grants to grow their businesses. To measure how much community members know about these entrepreneurs, she will ask neighbors the same set of 10 questions about the person’s business acumen, work ethic, profitability, and intelligence, among other qualities.

Friends and neighbors can be valuable sources of information, but Rigol also recognizes that these acquaintances may not always be entirely honest. She randomly varies how these 10 questions are asked, to assess whether people will lie to favor their friends and family, and whether different economic strategies can incentivize people to tell the truth about what they know. The questions can be asked in front of the other neighbors or in private; with or without monetary incentives to answer truthfully; and with or without being told that the answers will directly affect whether their neighbor is deemed eligible for a $100 grant. She then compares responses across the different groups to assess how helpful the community information was in identifying successful entrepreneurs under the different circumstances.

She piloted the project this summer, and data collection is just starting. After analyzing the information, Rigol hopes to find the perfect equation for getting truthful, useful banking information from community members: Maybe it’s asking the 10 questions in private, with no financial incentive, and under the guise that the answers won’t directly affect anyone. Or maybe it’s a different combination of factors.

Breaking cycles

Sometimes the personal impetus for her research is hard for Rigol’s parents to understand.

“They tell me, ‘Natalia, we worked so hard to get you out of these environments, why do you want to go back?’” she says. “They’re really very supportive, but I think they do worry.”

Rigol is committed to her work, even if it worries her parents. She’s not someone who loves research just for its own sake — she strives to ask questions that impact people’s problems, not just those that are interesting to her — and thinks that rigorous investigation is crucial to decision-making.

Next year, Rigol will continue her community-based banking work as a postdoc at Harvard. In her eyes, having access to financial tools is a first and crucial step in empowering people to achieve their goals. While her study highlights entrepreneurs, the project will speak to whether community information can be used to target other services, such as education loans for motivated students, government subsidies for the poor, or even health insurance.